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Next-Generation Sequencing Techniques for Eukaryotic Microorganisms: Sequencing-Based Solutions to Biological Problems

机译:真核微生物的下一代测序技术:基于序列的生物学问题解决方案

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Over the past 5 years, large-scale sequencing has been revolutionized by the development of several so-called next-generation sequencing (NGS) technologies. These have drastically increased the number of bases obtained per sequencing run while at the same time decreasing the costs per base. Compared to Sanger sequencing, NGS technologies yield shorter read lengths; however, despite this drawback, they have greatly facilitated genome sequencing, first for prokaryotic genomes and within the last year also for eukaryotic ones. This advance was possible due to a concomitant development of software that allows the de novo assembly of draft genomes from large numbers of short reads. In addition, NGS can be used for metagenomics studies as well as for the detection of sequence variations within individual genomes, e.g., single-nucleotide polymorphisms (SNPs), insertions/deletions (indels), or structural variants. Furthermore, NGS technologies have quickly been adopted for other high-throughput studies that were previously performed mostly by hybridization-based methods like microarrays. This includes the use of NGS for transcriptomics (RNA-seq) or the genome-wide analysis of DNA/protein interactions (ChIP-seq). This review provides an overview of NGS technologies that are currently available and the bioinformatics analyses that are necessary to obtain information from the flood of sequencing data as well as applications of NGS to address biological questions in eukaryotic microorganisms.
机译:在过去的5年中,大规模测序已通过几种所谓的下一代测序(NGS)技术的发展而发生了革命。这些大大增加了每次测序获得的碱基数量,同时降低了每个碱基的成本。与Sanger测序相比,NGS技术产生的读取长度更短;然而,尽管有这个缺点,但它们极大地促进了基因组测序,首先是原核基因组,最后一年是真核基因组。伴随着软件的开发,该进展是可能的,该软件允许从大量短读中 de novo 组装基因组草图。另外,NGS可用于宏基因组学研究以及检测单个基因组内的序列变异,例如单核苷酸多态性(SNP),插入/缺失(indels)或结构变体。此外,NGS技术已被其他高通量研究迅速采用,这些研究以前主要通过基于杂交的方法(如微阵列)进行。这包括使用NGS进行转录组学(RNA-seq)或DNA /蛋白质相互作用的全基因组分析(ChIP-seq)。这篇综述概述了目前可用的NGS技术以及为从大量测序数据中获取信息以及NGS应用于解决真核微生物中的生物学问题所必需的生物信息学分析。

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